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| 2022-09-20 | NIST Interagency Report 8292 Draft Supplement: FRVT Part 4: MORPH - Performance of Automated Face Morph Detection PDF |
| 2022-07-28 | NIST Interagency Report 8430: FRVT Part 4A: Utility of 1:N Face Recognition Algorithms for Morph Detection PDF |
The table provides a summary of all algorithms measured on attack presentation classification error rate (APCER) when bona fide classification error rate (BPCER) is set to 0.1 and 0.01, across a subset of the different morphing datasets used in our evaluation. APCER, or morph miss rate, is the proportion of morphs that are incorrectly classified as bona fides (nonmorphs). BPCER, or false detection rate, is the proportion of bona fides falsely classified as morphs.
The table below provides numerical tabulation of MMPMR and FNMR for recent face recognition algorithms submitted to FRVT MORPH and FRVT 1:1, ordered initially by FNMR.
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Global Morph
Local Morph
Local Morph Colorized Average
Local Morph Colorized Match